Epilepsy, a neurological disorder characterized by the occurrence of seizures (specifically episodic impairment or loss of consciousness, abnormal motor phenomena, psychic or sensory disturbances, or the perturbation of the autonomic nervous system), is debilitating to a great number of people. The prevalence of epilepsy is 0.7% of the population with as many as two million Americans that suffer from various forms of epilepsy and around 50 million worldwide. Research has found that its prevalence may be even greater worldwide, particularly in less economically developed nations, suggesting that the worldwide figure for epilepsy sufferers may be in excess of one hundred million.
A typical epilepsy patient experiences episodic attacks or seizures, which are generally defined as periods of abnormal neurological activity. The characteristics of an epileptic seizure onset are different from patient to patient, but are frequently consistent from seizure to seizure within a single patient. Because epilepsy is characterized by seizures, its sufferers are frequently limited in the kinds of activities they may participate in. Epilepsy can prevent people from driving, working, or otherwise participating in much of what society has to offer. Some epilepsy sufferers have serious seizures so frequently that they are effectively incapacitated. Furthermore, epilepsy is often progressive and can be associated with degenerative disorders and conditions. Over time, epileptic seizures often become more frequent and more serious, and may lead to deterioration of other brain functions (including cognitive function) as well as physical impairments.
Timely detection of seizures allows a caregiver to monitor their severity and duration and to determine whether immediate treatment is necessary. Attempts have been made to create alarm systems based on motion systems, which alert a caregiver or call for emergency services in response to a repetitive rhythmic movement, which could indicate a seizure. One example is described in U.S. Pat. No. 6,361,508. However, these systems suffer from an abundance of false alarms, since rhythmic movement is also associated with many types of everyday activity, such as walking, hand gesturing, and even typing. Most known systems are placed under the mattress of a patient, and are unsuitable for wear during an active day. An example is described in U.S. Pat. No. 4,320,766.
Nijsen et al. compared the efficiency of accelerometers to detect seizures to that found using EEG and video readings (Nijsen et al., Epilepsy & Behavior 7, (2005), 74-84), and stated that accelerometers do not require patients to be stationary as does EEG equipment, which is most readily available in hospitals. Nijsen performed visual analysis of the plotted signals (as presented on a chart recorder) but did not perform any numerical or statistical analysis on the accelerometer readings which would allow an accelerometer to be used as a stand-alone detection method. Use of an accelerometer alone, without statistical analysis, would result in a high degree of false positives due to rhythmic movement present in many everyday activities. As stated in Nijsen, “Visual analysis of ACM [accelerometer] readings is very labor intensive . . . it is more difficult to find suitable parameters that make computerized detection possible”. Nijsen therefore recognized the need to develop a computerized system which would serve as an alert system allowing normal ambulation.
Other systems, such as WO 03/001996, necessitate implanted electrodes, and rely on EEG readings obtained from the brain. Another type of system is described in WO 02/082999A1, which describes computerized analysis of video images taken of the patient in order to determine whether movement shown in a series of images is similar to that of an epileptic seizure.
The need exists for an improved method, and system for detecting an epileptic event in an epilepsy sufferer. The system should not interfere with everyday activities, and should allow freedom of movement. Such an improved system should have a low rate of false positive alerts, yet should successfully detect epileptic seizures when they occur.